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BUG: expanding_{cov,corr} for objects of different lengths #7541

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BUG: expanding_{cov,corr} for objects of different lengths #7541

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fff5ada
GH 7512 - bug in expanding_{cov,corr} for objects of different lengths
Jun 21, 2014
3adc7b2
fixed __flex_binary_moment() to deal with mismatched index sets
Jun 21, 2014
f593426
Merge remote-tracking branch 'upstream/master'
Jun 22, 2014
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24 changes: 12 additions & 12 deletions pandas/stats/moments.py
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Original file line number Diff line number Diff line change
Expand Up @@ -209,11 +209,11 @@ def rolling_cov(arg1, arg2=None, window=None, min_periods=None, freq=None,
pairwise = True if pairwise is None else pairwise # only default unset
arg1 = _conv_timerule(arg1, freq, how)
arg2 = _conv_timerule(arg2, freq, how)
window = min(window, len(arg1), len(arg2))

def _get_cov(X, Y):
mean = lambda x: rolling_mean(x, window, min_periods, center=center)
count = rolling_count(X + Y, window, center=center)
adj_window = min(window, len(X), len(Y))
mean = lambda x: rolling_mean(x, adj_window, min_periods, center=center)
count = rolling_count(X + Y, adj_window, center=center)
bias_adj = count / (count - 1)
return (mean(X * Y) - mean(X) * mean(Y)) * bias_adj
rs = _flex_binary_moment(arg1, arg2, _get_cov, pairwise=bool(pairwise))
Expand All @@ -234,14 +234,14 @@ def rolling_corr(arg1, arg2=None, window=None, min_periods=None, freq=None,
pairwise = True if pairwise is None else pairwise # only default unset
arg1 = _conv_timerule(arg1, freq, how)
arg2 = _conv_timerule(arg2, freq, how)
window = min(window, len(arg1), len(arg2))

def _get_corr(a, b):
num = rolling_cov(a, b, window, min_periods, freq=freq,
adj_window = min(window, len(a), len(b))
num = rolling_cov(a, b, adj_window, min_periods, freq=freq,
center=center)
den = (rolling_std(a, window, min_periods, freq=freq,
den = (rolling_std(a, adj_window, min_periods, freq=freq,
center=center) *
rolling_std(b, window, min_periods, freq=freq,
rolling_std(b, adj_window, min_periods, freq=freq,
center=center))
return num / den
return _flex_binary_moment(arg1, arg2, _get_corr, pairwise=bool(pairwise))
Expand All @@ -261,9 +261,9 @@ def _flex_binary_moment(arg1, arg2, f, pairwise=False):
results = {}
if isinstance(arg2, DataFrame):
X, Y = arg1.align(arg2, join='outer')
X = X + 0 * Y
Y = Y + 0 * X
if pairwise is False:
X = X + 0 * Y
Y = Y + 0 * X
res_columns = arg1.columns.union(arg2.columns)
for col in res_columns:
if col in X and col in Y:
Expand All @@ -276,7 +276,7 @@ def _flex_binary_moment(arg1, arg2, f, pairwise=False):
# Symmetric case
results[k1][k2] = results[k2][k1]
else:
results[k1][k2] = f(arg1[k1], arg2[k2])
results[k1][k2] = f(*_prep_binary(arg1[k1], arg2[k2]))
return Panel.from_dict(results).swapaxes('items', 'major')
else:
raise ValueError("'pairwise' is not True/False")
Expand Down Expand Up @@ -917,7 +917,7 @@ def expanding_cov(arg1, arg2=None, min_periods=1, freq=None, center=False,
min_periods = arg2
arg2 = arg1
pairwise = True if pairwise is None else pairwise
window = max(len(arg1), len(arg2))
window = len(arg1) + len(arg2)
return rolling_cov(arg1, arg2, window,
min_periods=min_periods, freq=freq,
center=center, pairwise=pairwise)
Expand All @@ -935,7 +935,7 @@ def expanding_corr(arg1, arg2=None, min_periods=1, freq=None, center=False,
min_periods = arg2
arg2 = arg1
pairwise = True if pairwise is None else pairwise
window = max(len(arg1), len(arg2))
window = len(arg1) + len(arg2)
return rolling_corr(arg1, arg2, window,
min_periods=min_periods,
freq=freq, center=center, pairwise=pairwise)
Expand Down
37 changes: 37 additions & 0 deletions pandas/stats/tests/test_moments.py
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Original file line number Diff line number Diff line change
Expand Up @@ -759,6 +759,43 @@ def test_expanding_corr_pairwise(self):
for i in result.items:
assert_almost_equal(result[i], rolling_result[i])

def test_expanding_cov_diff_length(self):
s1 = Series([1, 2, 3], index=[0, 1, 2])
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put the reference issue as a comment in the tests

s2 = Series([1, 3], index=[0, 2])
result = mom.expanding_cov(s1, s2)
expected = Series([None, None, 2.0])
assert_series_equal(result, expected)

s2a = Series([1, None, 3], index=[0, 1, 2])
result = mom.expanding_cov(s1, s2a)
assert_series_equal(result, expected)

def test_expanding_corr_diff_length(self):
s1 = Series([1, 2, 3], index=[0, 1, 2])
s2 = Series([1, 3], index=[0, 2])
result = mom.expanding_corr(s1, s2)
expected = Series([None, None, 1.0])
assert_series_equal(result, expected)

s2a = Series([1, None, 3], index=[0, 1, 2])
result = mom.expanding_corr(s1, s2a)
assert_series_equal(result, expected)

def test_expanding_corr_pairwise_diff_length(self):
df1 = DataFrame([[1,2], [3, 2], [3,4]], columns=['A','B'])
df1a = DataFrame([[1,2], [3,4]], index=[0,2], columns=['A','B'])
df2 = DataFrame([[5,6], [None,None], [2,1]], columns=['X','Y'])
df2a = DataFrame([[5,6], [2,1]], index=[0,2], columns=['X','Y'])
result1 = mom.expanding_corr(df1, df2, pairwise=True)[2]
result2 = mom.expanding_corr(df1, df2a, pairwise=True)[2]
result3 = mom.expanding_corr(df1a, df2, pairwise=True)[2]
result4 = mom.expanding_corr(df1a, df2a, pairwise=True)[2]
expected = DataFrame([[-1.0, -1.0], [-1.0, -1.0]], index=['A','B'], columns=['X','Y'])
assert_frame_equal(result1, expected)
assert_frame_equal(result2, expected)
assert_frame_equal(result3, expected)
assert_frame_equal(result4, expected)

def test_rolling_skew_edge_cases(self):

all_nan = Series([np.NaN] * 5)
Expand Down